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quest-run
Run quest phases with automated execution loop
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
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Run quest phases with automated execution loop
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
| name | quest-run |
| description | Run quest phases with automated execution loop |
| allowed-tools | Bash, Read, Write, Edit, Task |
Automates quest phase execution. Each phase runs in a fresh subagent context to prevent token accumulation. The orchestrator stays lean — reads state files, reviews JSON returns, delegates everything.
/quest-run Run from current phase to completion
/quest-run 3 Start from phase 3
/quest-run 3-5 Run phases 3 through 5 only
Find active quest:
.planning/*/QUEST.md files with Status: active/quest-create firstRead quest state from the active quest directory:
PHASES.md — Phase list and statusesSTATE.md — Current positionconfig.json — Settings (maxRetries)Determine phase range:
pending phase to last phaseFor each phase in range:
a. Read phase status from PHASES.md — skip if completed
b. Spawn fresh subagent via Task tool:
Task tool with subagent_type: phase-executor
Include in the prompt:
phases/NN-name/DIAGNOSIS.mdc. On subagent return, parse the JSON summary:
status=completed:
completedstatus=needs_retry:
phases/NN-name/DIAGNOSIS.mdcheckpoint in PHASES.mdstatus=error:
When all phases complete:
/quest-completeFor each phase, spawn with this prompt:
Execute phase {N} of the quest "{quest-name}".
## Quest Context
{QUEST.md summary — goal, repos, key dependencies}
## Phase Goal
{Phase N goal from PHASES.md}
## Previous Phases
{Brief summary of completed phases — what was done, key commits}
## Instructions
Run the full phase lifecycle:
1. If no PLAN.md exists in phases/{NN}-{name}/: research codebase, create PLAN.md
2. Execute each task with atomic commits (conventional format)
3. Verify: goal-backward check (artifacts exist, are substantive, are wired)
4. If verify fails: fix and re-verify (up to 2 internal retries)
Write PLAN.md to: {quest-dir}/phases/{NN}-{name}/PLAN.md
Before implementing crypto, signing, or wallet operations: check available MCP tools first.
Return JSON:
{
"status": "completed" | "needs_retry" | "error",
"phase": N,
"commits": ["sha: message", ...],
"retries": 0,
"summary": "Brief description",
"diagnosis": "Only if needs_retry — what went wrong and suggested fix"
}
For retries, append:
## Previous Attempt Diagnosis
{Contents of DIAGNOSIS.md}
Focus on fixing the identified issues. Do not redo completed work.
When a phase hits maxRetries:
/quest-run to continue/quest-run {N+1}Show progress as phases run:
Running quest: Cost Tracking
Starting from phase 1 of 5
Phase 1: Add cost schema
Spawning subagent...
Completed (2 commits)
Phase 2: Capture costs
Spawning subagent...
Completed (3 commits, 1 retry)
Phase 3: Add margin query
Spawning subagent...
needs_retry → retrying (attempt 2/3)...
Completed (2 commits)
Quest complete! 5/5 phases, 2 retries total.
Use /quest-complete to archive.
Why subagents per phase? Each phase can consume significant context during planning (codebase exploration), execution (file edits), and verification (artifact checking). Running all phases in one context leads to token exhaustion.
How it works:
| Component | Budget |
|---|---|
| Orchestrator | ~10% (reads state files, spawns subagents) |
| Phase subagent | Fresh 200k per phase |
| State persistence | Quest directory files (no token cost) |
Status: activependingReview open issues and PRs across aibtcdev repos with prioritized next steps
Evaluate session context through Arc's editorial lens and draft social posts
Create, update, and publish blog posts on arc0.me in Arc's voice
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Play Floor is Lava on Scrapyard arena as Arc (arc0btc). Interactive AI agent game on Stacks.
Mark the current quest as complete and archive it